8991555
1935
Hilde Weerts
3481
Supervised Classification
8317
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1)
6927110
categorical_features
[]
7644
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
7644
handle_unknown
"ignore"
7644
n_values
"auto"
7644
sparse
true
7644
threshold
0.0
7645
copy
true
7646
with_mean
false
7646
with_std
true
7646
C
0.4784301353425586
7650
cache_size
200
7650
class_weight
null
7650
coef0
0.1968190084970649
7650
decision_function_shape
"ovr"
7650
degree
3
7650
gamma
0.00035564910488405363
7650
kernel
"rbf"
7650
max_iter
-1
7650
probability
false
7650
random_state
1
7650
shrinking
false
7650
tol
6.127397202936418e-05
7650
verbose
false
7650
axis
0
8316
categorical_features
[]
8316
copy
true
8316
fill_empty
0
8316
missing_values
"NaN"
8316
strategy
"mean"
8316
strategy_nominal
"most_frequent"
8316
verbose
0
8316
memory
null
8317
openml-python
Sklearn_0.19.1.
study_98
300
isolet
https://www.openml.org/data/download/52405/phpB0xrNj
-1
18898071
description
https://api.openml.org/data/download/18898071/description.xml
-1
18898072
predictions
https://api.openml.org/data/download/18898072/predictions.arff
area_under_roc_curve
0.9721896493448081 [0.990733,0.955798,0.990933,0.951733,0.951333,0.983366,0.972266,0.991667,0.993,0.992666,0.984266,0.994133,0.958804,0.925466,0.981467,0.927666,0.996133,0.9964,0.969667,0.922533,0.981066,0.929866,0.996733,0.986533,0.993267,0.959466]
average_cost
0
f_measure
0.9464592315912252 [0.968801,0.86385,0.973597,0.912752,0.903654,0.947541,0.946667,0.991597,0.985025,0.976898,0.966777,0.97377,0.896104,0.891986,0.976351,0.870152,0.983498,0.990033,0.960818,0.897527,0.966555,0.883959,0.959872,0.983165,0.991625,0.945205]
kappa
0.9443786464984634
kb_relative_information_score
7374.98691642699
mean_absolute_error
0.00411400834640541
mean_prior_absolute_error
0.07396449117237175
number_of_instances
7797 [300,300,300,300,300,298,300,300,300,300,300,300,299,300,300,300,300,300,300,300,300,300,300,300,300,300]
precision
0.9474711460797436 [0.954693,0.814159,0.964052,0.918919,0.900662,0.926282,0.946667,1,0.983389,0.96732,0.963576,0.958065,0.870662,0.934307,0.989726,0.880546,0.973856,0.986755,0.982578,0.954887,0.969799,0.905594,0.925697,0.993197,0.996633,0.971831]
predictive_accuracy
0.9465178914967295
prior_entropy
4.700438289429255
recall
0.9465178914967295 [0.983333,0.92,0.983333,0.906667,0.906667,0.969799,0.946667,0.983333,0.986667,0.986667,0.97,0.99,0.923077,0.853333,0.963333,0.86,0.993333,0.993333,0.94,0.846667,0.963333,0.863333,0.996667,0.973333,0.986667,0.92]
relative_absolute_error
0.05562139725693309
root_mean_prior_squared_error
0.19230768465256318
root_mean_squared_error
0.06414053590675253
root_relative_squared_error
0.3335307999918642
total_cost
0
area_under_roc_curve
0.9713333333333333 [0.981333,0.948,0.998667,0.980667,0.948,0.999333,0.948667,0.983333,1,0.999333,0.965333,0.999333,0.948667,0.948667,0.983333,0.915333,1,1,0.999333,0.898,0.981333,0.946667,0.998667,0.966667,0.983333,0.932667]
area_under_roc_curve
0.9726666666666666 [0.981333,0.963333,1,0.949333,0.979333,0.998667,0.982667,0.983333,0.982667,0.998667,0.965333,0.998667,0.965333,0.965333,0.966667,0.88,0.999333,0.999333,0.966667,0.916,0.966667,0.931333,0.999333,0.983333,1,0.966667]
area_under_roc_curve
0.9700000000000002 [0.998667,0.947333,0.982667,0.914,0.947333,0.981333,0.966667,0.983333,0.966,0.983333,0.964667,0.983333,0.981333,0.932667,0.999333,0.93,1,0.982667,0.949333,0.914,0.999333,0.981333,0.998667,0.983333,0.999333,0.95]
area_under_roc_curve
0.9740000000000002 [0.999333,0.995333,0.982667,0.982667,0.983333,0.998667,0.997333,0.983333,1,0.982667,0.998667,0.983333,0.945333,0.898,0.999333,0.898,0.982667,1,0.983333,0.9,0.982667,0.866,0.999333,0.982667,1,0.999333]
area_under_roc_curve
0.9653333333333337 [0.998667,0.925333,0.982,0.981333,0.948,0.946667,0.998,1,0.982667,0.983333,1,0.983333,0.996,0.883333,0.999333,0.966,0.999333,0.999333,0.915333,0.916667,0.982667,0.831333,0.981333,0.983333,0.983333,0.932]
area_under_roc_curve
0.9806666666666668 [1,0.98,1,0.949333,0.966,0.982667,0.982667,1,1,0.999333,1,0.999333,0.947333,0.932,0.983333,0.898,1,1,1,0.949333,1,0.947333,0.998667,0.982667,1,0.999333]
area_under_roc_curve
0.9680000000000001 [0.982667,0.962667,0.999333,0.948,0.864,0.982,0.998667,0.983333,0.999333,0.999333,0.982667,0.998,0.913333,0.914,0.966667,0.914,0.982667,0.983333,0.966667,0.949333,0.965333,0.966,0.996667,1,0.983333,0.966667]
area_under_roc_curve
0.9739724076546505 [0.999332,0.929328,0.983333,0.931998,0.94733,0.998665,0.949332,1,1,0.999332,1,0.998665,0.960184,0.848665,0.966667,0.997997,1,1,0.966667,0.915999,0.999332,0.949332,0.998665,1,1,0.981998]
area_under_roc_curve
0.9712968402314196 [1,0.943992,0.982666,0.930663,0.947997,0.981425,0.965999,1,1,0.983333,0.999332,0.999332,0.965332,0.965999,0.983333,0.92866,0.997997,0.999332,0.983333,0.883333,0.95,0.931331,0.997997,1,1,0.932666]
area_under_roc_curve
0.9746355140186916 [0.965999,0.962661,0.997997,0.949332,0.981998,0.963517,0.932666,1,0.999332,0.997997,0.966667,0.997997,0.965332,0.965999,0.966667,0.948665,0.999332,1,0.965999,0.982666,0.983333,0.947997,0.997997,0.983333,0.983333,0.933333]
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
f_measure
0.9445317415884686 [0.935484,0.9,0.967742,0.920635,0.9,0.983607,0.915254,0.983051,1,0.983607,0.933333,0.983607,0.915254,0.915254,0.983051,0.877193,1,1,0.983607,0.842105,0.935484,0.870968,0.967742,0.965517,0.983051,0.912281]
f_measure
0.9473300357926128 [0.935484,0.888889,1,0.931034,0.892308,0.967742,0.966667,0.983051,0.966667,0.967742,0.933333,0.967742,0.933333,0.933333,0.965517,0.793103,0.983607,0.983607,0.965517,0.892857,0.965517,0.881356,0.983607,0.983051,1,0.965517]
f_measure
0.9422901588184022 [0.967742,0.885246,0.966667,0.847458,0.885246,0.935484,0.965517,0.983051,0.949153,0.983051,0.918033,0.983051,0.935484,0.912281,0.983607,0.852459,1,0.966667,0.931034,0.847458,0.983607,0.935484,0.967742,0.983051,0.983607,0.947368]
f_measure
0.9493143835698502 [0.983607,0.895522,0.966667,0.966667,0.983051,0.967742,0.9375,0.983051,1,0.966667,0.967742,0.983051,0.84375,0.842105,0.983607,0.842105,0.966667,1,0.983051,0.888889,0.966667,0.830189,0.983607,0.966667,1,0.983607]
f_measure
0.9329869576191387 [0.967742,0.764706,0.95082,0.935484,0.9,0.870968,0.952381,1,0.966667,0.983051,1,0.983051,0.909091,0.867925,0.983607,0.949153,0.983607,0.983607,0.877193,0.909091,0.966667,0.754717,0.935484,0.983051,0.983051,0.896552]
f_measure
0.962624336674511 [1,0.90625,1,0.931034,0.949153,0.966667,0.966667,1,1,0.983607,1,0.983607,0.885246,0.896552,0.983051,0.842105,1,1,1,0.931034,1,0.885246,0.967742,0.966667,1,0.983607]
f_measure
0.9381933328255614 [0.966667,0.875,0.983607,0.9,0.785714,0.95082,0.967742,0.983051,0.983607,0.983607,0.966667,0.952381,0.833333,0.847458,0.965517,0.847458,0.966667,0.983051,0.965517,0.931034,0.933333,0.949153,0.923077,1,0.983051,0.965517]
f_measure
0.9494804624545882 [0.983607,0.83871,0.983051,0.896552,0.885246,0.967742,0.931034,1,1,0.983607,1,0.967742,0.84375,0.792453,0.965517,0.952381,1,1,0.965517,0.892857,0.983607,0.931034,0.967742,1,1,0.95082]
f_measure
0.9450472999433794 [1,0.818182,0.966667,0.866667,0.9,0.949153,0.949153,1,1,0.983051,0.983607,0.983607,0.933333,0.949153,0.983051,0.825397,0.952381,0.983607,0.983051,0.867925,0.947368,0.881356,0.952381,1,1,0.912281]
f_measure
0.9512999176537987 [0.949153,0.875,0.952381,0.931034,0.95082,0.915254,0.912281,1,0.983607,0.952381,0.965517,0.952381,0.933333,0.949153,0.965517,0.915254,0.983607,1,0.949153,0.966667,0.983051,0.9,0.952381,0.983051,0.983051,0.928571]
kappa
0.9426666666666667
kappa
0.9453333333333332
kappa
0.94
kappa
0.948
kappa
0.9306666666666666
kappa
0.9613333333333334
kappa
0.9359999999999999
kappa
0.9479336973398731
kappa
0.9425930718199284
kappa
0.9492682960269133
kb_relative_information_score
736.4847466945296
kb_relative_information_score
738.5095778015775
kb_relative_information_score
734.4608927616237
kb_relative_information_score
740.5324477288402
kb_relative_information_score
727.3744673504021
kb_relative_information_score
750.6497357190805
kb_relative_information_score
731.4211946263213
kb_relative_information_score
739.5325243030977
kb_relative_information_score
735.4818338717328
kb_relative_information_score
740.5394955690854
mean_absolute_error
0.0042406311637080895
mean_absolute_error
0.004043392504930968
mean_absolute_error
0.00443786982248521
mean_absolute_error
0.0038461538461538477
mean_absolute_error
0.0051282051282051325
mean_absolute_error
0.002859960552268244
mean_absolute_error
0.004733727810650891
mean_absolute_error
0.003851091142490374
mean_absolute_error
0.004246074849412465
mean_absolute_error
0.003752345215759851
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396448587535052
mean_prior_absolute_error
0.07396447325283656
mean_prior_absolute_error
0.07396447325283656
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,30,30,30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
precision
0.9455853915427053 [0.90625,0.9,0.9375,0.878788,0.9,0.967742,0.931034,1,1,0.967742,0.933333,0.967742,0.931034,0.931034,1,0.925926,1,1,0.967742,0.888889,0.90625,0.84375,0.9375,1,1,0.962963]
precision
0.9490834572396885 [0.90625,0.848485,1,0.964286,0.828571,0.9375,0.966667,1,0.966667,0.9375,0.933333,0.9375,0.933333,0.933333,1,0.821429,0.967742,0.967742,1,0.961538,1,0.896552,0.967742,1,1,1]
precision
0.9435032291226673 [0.9375,0.870968,0.966667,0.862069,0.870968,0.90625,1,1,0.965517,1,0.903226,1,0.90625,0.962963,0.967742,0.83871,1,0.966667,0.964286,0.862069,0.967742,0.90625,0.9375,1,0.967742,1]
precision
0.9525980253034539 [0.967742,0.810811,0.966667,0.966667,1,0.9375,0.882353,1,1,0.966667,0.9375,1,0.794118,0.888889,0.967742,0.888889,0.966667,1,1,1,0.966667,0.956522,0.967742,0.966667,1,0.967742]
precision
0.937769522798488 [0.9375,0.684211,0.935484,0.90625,0.9,0.84375,0.909091,1,0.966667,1,1,1,0.833333,1,0.967742,0.965517,0.967742,0.967742,0.925926,1,0.966667,0.869565,0.90625,1,1,0.928571]
precision
0.9633519790078547 [1,0.852941,1,0.964286,0.965517,0.966667,0.966667,1,1,0.967742,1,0.967742,0.870968,0.928571,1,0.888889,1,1,1,0.964286,1,0.870968,0.9375,0.966667,1,0.967742]
precision
0.93972054826684 [0.966667,0.823529,0.967742,0.9,0.846154,0.935484,0.9375,1,0.967742,0.967742,0.966667,0.909091,0.833333,0.862069,1,0.862069,0.966667,1,1,0.964286,0.933333,0.965517,0.857143,1,1,1]
precision
0.9520362289256311 [0.967742,0.8125,1,0.928571,0.870968,0.9375,0.964286,1,1,0.967742,1,0.9375,0.771429,0.913043,1,0.909091,1,1,1,0.961538,0.967742,0.964286,0.9375,1,1,0.935484]
precision
0.9480895175068275 [1,0.75,0.966667,0.866667,0.9,0.933333,0.965517,1,1,1,0.967742,0.967742,0.933333,0.965517,1,0.787879,0.909091,0.967742,1,1,1,0.896552,0.909091,1,1,0.962963]
precision
0.9533644033713371 [0.965517,0.823529,0.909091,0.964286,0.935484,0.9,0.962963,1,0.967742,0.909091,1,0.909091,0.933333,0.965517,1,0.931034,0.967742,1,0.965517,0.966667,1,0.9,0.909091,1,1,1]
predictive_accuracy
0.9448717948717948
predictive_accuracy
0.9474358974358974
predictive_accuracy
0.9423076923076923
predictive_accuracy
0.95
predictive_accuracy
0.9333333333333332
predictive_accuracy
0.9628205128205128
predictive_accuracy
0.9384615384615383
predictive_accuracy
0.9499358151476252
predictive_accuracy
0.944801026957638
predictive_accuracy
0.951219512195122
prior_entropy
4.700438289429255
prior_entropy
4.700438289429255
prior_entropy
4.700438289429255
prior_entropy
4.700438289429255
prior_entropy
4.700438289429255
prior_entropy
4.700438289429255
prior_entropy
4.700438289429255
prior_entropy
4.700438289429255
prior_entropy
4.700438289429255
prior_entropy
4.700438289429255
recall
0.9448717948717948 [0.966667,0.9,1,0.966667,0.9,1,0.9,0.966667,1,1,0.933333,1,0.9,0.9,0.966667,0.833333,1,1,1,0.8,0.966667,0.9,1,0.933333,0.966667,0.866667]
recall
0.9474358974358974 [0.966667,0.933333,1,0.9,0.966667,1,0.966667,0.966667,0.966667,1,0.933333,1,0.933333,0.933333,0.933333,0.766667,1,1,0.933333,0.833333,0.933333,0.866667,1,0.966667,1,0.933333]
recall
0.9423076923076923 [1,0.9,0.966667,0.833333,0.9,0.966667,0.933333,0.966667,0.933333,0.966667,0.933333,0.966667,0.966667,0.866667,1,0.866667,1,0.966667,0.9,0.833333,1,0.966667,1,0.966667,1,0.9]
recall
0.95 [1,1,0.966667,0.966667,0.966667,1,1,0.966667,1,0.966667,1,0.966667,0.9,0.8,1,0.8,0.966667,1,0.966667,0.8,0.966667,0.733333,1,0.966667,1,1]
recall
0.9333333333333333 [1,0.866667,0.966667,0.966667,0.9,0.9,1,1,0.966667,0.966667,1,0.966667,1,0.766667,1,0.933333,1,1,0.833333,0.833333,0.966667,0.666667,0.966667,0.966667,0.966667,0.866667]
recall
0.9628205128205128 [1,0.966667,1,0.9,0.933333,0.966667,0.966667,1,1,1,1,1,0.9,0.866667,0.966667,0.8,1,1,1,0.9,1,0.9,1,0.966667,1,1]
recall
0.9384615384615385 [0.966667,0.933333,1,0.9,0.733333,0.966667,1,0.966667,1,1,0.966667,1,0.833333,0.833333,0.933333,0.833333,0.966667,0.966667,0.933333,0.9,0.933333,0.933333,1,1,0.966667,0.933333]
recall
0.9499358151476252 [1,0.866667,0.966667,0.866667,0.9,1,0.9,1,1,1,1,1,0.931034,0.7,0.933333,1,1,1,0.933333,0.833333,1,0.9,1,1,1,0.966667]
recall
0.944801026957638 [1,0.9,0.966667,0.866667,0.9,0.965517,0.933333,1,1,0.966667,1,1,0.933333,0.933333,0.966667,0.866667,1,1,0.966667,0.766667,0.9,0.866667,1,1,1,0.866667]
recall
0.9512195121951219 [0.933333,0.933333,1,0.9,0.966667,0.931034,0.866667,1,1,1,0.933333,1,0.933333,0.933333,0.933333,0.9,1,1,0.933333,0.966667,0.966667,0.9,1,0.966667,0.966667,0.866667]
relative_absolute_error
0.05733333333333302
relative_absolute_error
0.05466666666666636
relative_absolute_error
0.05999999999999967
relative_absolute_error
0.0519999999999997
relative_absolute_error
0.06933333333333297
relative_absolute_error
0.038666666666666426
relative_absolute_error
0.06399999999999967
relative_absolute_error
0.05206676010674188
relative_absolute_error
0.05740695042737462
relative_absolute_error
0.05073172363349384
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230767088031558
root_mean_prior_squared_error
0.19230763806177284
root_mean_prior_squared_error
0.19230763806177284
root_mean_squared_error
0.06512012871384769
root_mean_squared_error
0.06358767573147306
root_mean_squared_error
0.06661733875264915
root_mean_squared_error
0.06201736729460424
root_mean_squared_error
0.07161148740394332
root_mean_squared_error
0.0534785990118313
root_mean_squared_error
0.06880209161537817
root_mean_squared_error
0.06205716028380911
root_mean_squared_error
0.06516191256717735
root_mean_squared_error
0.0612563891831689
root_relative_squared_error
0.3386246559218025
root_relative_squared_error
0.33065590072856227
root_relative_squared_error
0.346410147815709
root_relative_squared_error
0.32249029717973615
root_relative_squared_error
0.37237971977552625
root_relative_squared_error
0.2780887038650852
root_relative_squared_error
0.35777086225266425
root_relative_squared_error
0.32269726943149835
root_relative_squared_error
0.3388420409294721
root_relative_squared_error
0.31853331360396714
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
usercpu_time_millis
86733.73792301572
usercpu_time_millis
94996.20807298925
usercpu_time_millis
85748.79390200658
usercpu_time_millis
80428.14114299836
usercpu_time_millis
76476.11799598963
usercpu_time_millis
82162.31894301018
usercpu_time_millis
77272.94128799986
usercpu_time_millis
76095.0257400109
usercpu_time_millis
76738.09294500097
usercpu_time_millis
75758.47393700678
usercpu_time_millis_testing
3584.707159010577
usercpu_time_millis_testing
3690.4898719949415
usercpu_time_millis_testing
3675.1872500026366
usercpu_time_millis_testing
3675.985338006285
usercpu_time_millis_testing
3505.2907219942426
usercpu_time_millis_testing
3652.3203670076327
usercpu_time_millis_testing
3604.6681600128068
usercpu_time_millis_testing
3865.097018002416
usercpu_time_millis_testing
3552.178270998411
usercpu_time_millis_testing
3527.249970007688
usercpu_time_millis_training
83149.03076400515
usercpu_time_millis_training
91305.7182009943
usercpu_time_millis_training
82073.60665200395
usercpu_time_millis_training
76752.15580499207
usercpu_time_millis_training
72970.82727399538
usercpu_time_millis_training
78509.99857600254
usercpu_time_millis_training
73668.27312798705
usercpu_time_millis_training
72229.92872200848
usercpu_time_millis_training
73185.91467400256
usercpu_time_millis_training
72231.2239669991